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Despite the considerable hype about how Big Data Analytics (BDA) can transform businesses and advance their capabilities, recognising its strategic value through successful adoption is yet to be appreciated. The purpose of this paper is to focus on the process-level value-chain realisation of BDA adoption between SMEs and large organisations.

Resource-based theory offered the lens for developing a conceptual BDA process-level value chain adoption model. A combined two-staged regression-artificial neural network approach has been utilised for 369 small, medium (SMEs) and large organisations to verify their critical value chain process-level drivers for successful organisational adoption of BDA.

The findings revealed that organisational BDA adoption success is driven predominantly by product—and service-process-level value, with distinctive discrepancies dependent on the organisation’s size. Large organisations primarily embrace BDA for their external value chain dimensions, while SMEs encompass its internal value chain cues. As such, businesses will be advised to acknowledge their organisational dynamics and precise size to develop the right strategies to adopt BDA successfully.

The study advances the understanding of the role of internal and external value chain drivers in influencing how BDA can be successfully adopted in SMEs and large organisations. Thus, appreciating the organisation’s unique attributes, including its size, will need to be carefully examined. By investigating these elements, this research has shed new light on how developing such innovative capabilities and competencies must be carefully crafted to help create a sustainable competitive advantage.

For an organisational positioning, acknowledging the role of internal and external value chain drivers is critical for implementing the right strategies for adopting BDA. For larger businesses, resources for innovation often can be widely available compared to SMEs. As such, they can manage their costs and associated risks resourcefully. By considering the identified value-chain-related adoption success factors, businesses should be better positioned to assess their competencies while being prepared to adopt BDA.

The study offers the research and business community empirical-based insights into the strategies needed to successfully adopt big data in an organisation from a process-level value chain perspective.

The purpose of this paper is to fill a gap in the literature regarding the open innovation management approaches that small and medium-sized enterprises (SMEs) can use to access digital technologies and incorporate them into their organizational processes. The research question is: What organizational and process-level managerial actions do SMEs take to successfully access and implement digital technologies within their organizational processes?

Using Guertler et al.'s (2020) Action Innovation Management Research (AIM-R) framework, this study examines the digital transformation experiences of 10 European SMEs to gain insights into the managerial actions that foster successful digital transformation.

The findings of the paper reveal two major contributions. First, a digital transformation roadmap for SMEs is proposed, with a focus on accessing external resources and reconfiguring internal ones to ease their digital transformation journey. Second, three distinct paradoxes that influence the digital transformation process in SMEs are highlighted, providing useful insights into the challenges and tensions SMEs face during this journey.

This paper provides a unique perspective on the digital transformation of SMEs by examining the managerial actions required for successful technology adoption and revealing the paradoxes that may emerge during this transformative process. The findings form the basis for future research, deepening our understanding of digital transformation in SMEs and providing actionable advice to managers and practitioners navigating this journey.

Alternative theoretical perspectives on performance measurement and management (PMM) have been advanced in response to shortcomings observed with the dominant control systems-based paradigm. The purpose of this investigation is to ascertain whether one such perspective, rooted in social systems theory and practice theory, can accommodate these shortcomings and positively impact organisational effectiveness (OE) and performance.

Longitudinal critical realism-based case study research is employed in action research mode to investigate how adopting a social complexity perspective on PMM affected the behaviour and performance of a commercial organisation.

The case study observations suggest that by putting people and their behaviour and organisational practices at the centre of PMM, near-term organisational outcomes can be influenced favourably in complex and dynamic environments.

This investigation provides a tool for undertaking a social complexity interpretation of PMM.

This research supports the proposal that complexity theory provides an alternative paradigm for managing performance in organisations and describes the first practical application of a social complexity interpretation of PMM. It presents a model for use and further development by other researchers.

This study explores the consequences of digitalization in the field of education, particularly in relation to teachers’ course processes in higher education institutions. It emphasizes the importance of understanding how information systems (IS) support not only individual tasks but also processes as a whole. The results reveal that process practices have not been considered comprehensively and even core processes may be unseen.

A systematic literature review was conducted to explore the extent to which teachers’ processes are discussed in the literature. A qualitative case study was then conducted at a Finnish higher education institution to identify course processes and their relationships to IS.

Teachers’ processes have scarcely been discussed in the literature, and the process support provided by ISs is remarkably limited. It seems that course processes, which are core to education, are a blind spot in education digitalization. To support evaluating the level of support by IS, novel course process indicators were introduced.

Developing core processes, teachers’ course processes and thesis processes in education field, supports improving service quality. In all industries, organizations should consider whether processes are properly recognized and whether IS support not only individual tasks but also processes as a whole. We recommend recognizing and applying business process management practices to better support teachers’ work and to improve overall efficiency in education.

To the best of our knowledge, this is the first education sector study that attends to teacher’s work as a comprehensive process.

This qualitative study aims to fill gaps in a widely studied and relevant organizational feature: the alignment between information technologies and business strategies.

This research is a qualitative study. The authors used focus groups, content analysis and semantic networks as research approaches to identify the main factors that prevent or foster such alignment.

Results reveal a leading role of innovation, organizational culture, access to information and financial factors that could promote or inhibit alignment and competitiveness.

This research was conducted only in small and medium organizations in Mexico, which represents about 52% of the Mexican Gross Domestic Product (for Mexico as one of the leading trade partners of the USA).

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

The purpose of this paper is to explore the integration of business intelligence (BI) systems in the digital transformation context and its impact on management control (MC) and organizational performance by delving into the implementation of a BI pilot project in a multinational Engineering and Construction (E&C) group.

This research adopts a qualitative insider action research approach. The initial stage of a BI system (BIS) is implemented by leveraging the critical success factors (CSFs) framework, based on the organizational, process and technological dimensions.

The results show that the BI solution leverages the capabilities of the reporting process with impacts on MC and overall organizational performance. The study uncovers the intricate dynamics of integrating BI and reports gains that span across streamlined and standardized processes, optimized use of resources, improved data flexibility and nurturing a data-driven culture.

This research adds to the current literature on MC and accounting information systems by providing an in-depth analysis of the early stages involved in implementing a BIS. The approach uses a well-established CSFs framework, which enhances the comprehension of how these factors impact the success of the implementation process. Focusing on the E&C sector, where the adoption of digital transformation is still gaining traction, this study provides practical knowledge and extends the theoretical understanding of BI technology applications with empirical evidence from the accounting field.

Despite the fact this is already known over how sports spectators interpret sponsorship content, less is known about participants’ sentiments toward sponsors, which are sometimes crucial to the survival of participation sporting events. Various researchers have examined at how spectators recognize or recall sponsors, but very few have explored it from the viewpoint of sport participants. This research portrays a shift in focus from spectator-based to participant-based marketing by studying the differences over how participants and spectators perceive sport sponsorship, recognizing the current knowledge gap regarding the process of sponsorship in participant-based sports. Sponsorship previous research has focused on the effectiveness of sport sponsorships utilizing variables such sponsor recognition, desire to sponsors’ products and anticipated sponsorship advantages (Koronios and Dimitropoulos, 2020). The examination of sport sponsorship from the standpoint of the sport spectator is something that many of the past studies have in common. The application of past research analysing sport sponsorship from a distinct perspective: that of the sport participant, distinguishes the present study. In addition, the present study explores the distinctions in sponsorship effectiveness between spectators and participants, a topic which hasn't been addressed at before in sponsorship literature.

This study depicts a move away from spectator-based to participant-based marketing, utilizing contemporary implicit physiological variables to measure participants’ and spectators’ awareness of and attitude toward sponsors, and it proposes a model of their purchase intentions toward real sponsors of a martial event. A total of 1,332 questionnaires were collected and analysed.

Factors such as sport involvement, social media use, sincerity and beliefs of sponsorship were found to have a significant effect on purchase intention of spectators and participants. And crucial differences in the significance of various antecedent factors between spectators and participants were detected in the formation of positive purchase and word-of-mouth intentions.

This paper gives prominence to contemporary methodological advances in the field of implicit social cognition and their relevance to sponsorship. This is the first sponsorship research which examines the effectiveness of sponsorship variables under the implicit–explicit variables dichotomy.

The application of lean and quality improvement methods is very common in process improvement projects at organisational levels. The purpose of this research is to assess the adoption of Lean Six Sigma™ approaches for addressing a complex process-related issue in the coal industry.

The sticky coal problem was investigated from the perspective of process-related issues. Issues were addressed using a blended Lean value stream of supply chain interfaces and waste minimisation through the Six Sigma™ DMAIC problem-solving approach, taking into consideration cross-organisational processes.

It was found that the tendency to “solve the problem” at the receiving location without communication to the upstream was, and is still, a common practice that led to the main problem of downstream issues. The application of DMAIC Six Sigma™ helped to address the broader problem. The overall operations were improved significantly, showing the reduction of sticky coal/wagon hang-up in the downstream coal handling terminal.

The Lean Six Sigma approaches were adopted using DMAIC across cross-organisational supply chain processes. However, blending Lean and Six Sigma methods needs to be empirically tested across other sectors.

The proposed methodology, using a framework of Lean Six Sigma approaches, could be used to guide practitioners in addressing similar complex and recurring issues in the manufacturing sector.

This research introduces a novel approach to process analysis, selection and contextualised improvement using a combination of Lean Six Sigma™ tools, techniques and methodologies sustained within a supply chain with certified ISO 9001 quality management systems.

Unlike traditional industries, the e-cigarette is an epoch-making innovative product originating in China and occupying an absolute competitive advantage in the international market. The traditional A-U model describes the laws and characteristics of technological innovation in developed countries. In contrast, the inverse A-U model depicts the process of “secondary innovation” in late-developing countries through digestion and absorption. This paper aims to find out that if the e-cigarette, as a “first innovation” industry in a late-developing country, conform to the A-U model or conform to the “inverse A-U model”.

This paper takes the patent data of e-cigarettes from 2004 to 2021 as the research object, and uses Python’s Jieba segment words to divide product innovation and process innovation, and then uses statistical analysis methods to conduct empirical analyses on these data.

Thus, an improved A-U model suitable for the e-cigarette industry is proposed. In this model, product innovation in the e-cigarette industry appeared earlier than process innovation, but the synchronous development of product and process innovation is not lagging. The improved A-U model in the e-cigarette industry is not only different from the traditional A-U model but also does not conform to the inverse A-U model.

It is conducive to expanding and clarifying the theoretical contribution and applicable boundaries of the A-U model and has sparked thinking and exploration of the A-U model in e-cigarettes and emerging industries.

On this basis, suggestions on the development path and countermeasures of the e-cigarette industry are put forward.

Based on the e-cigarette industry, this paper takes patents as the research object and provides the method of dividing product innovation and process innovation, and proposes an A-U model suitable for the e-cigarette industry on this basis. By comparing the traditional A-U model with the inverse A-U model in latecomer countries, the background and causes of e-cigarette A-U model heterogeneity are analyzed from different stages and overall morphology. Based on this, the heterogeneity characteristics of e-cigarette innovation are summarized and sorted out.